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Application of Support Vector Machines in Evaluating the Internationalization Success of Companies

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Rustam, Z and Yaurita, F and Segovia Vargas, María Jesús (2018) Application of Support Vector Machines in Evaluating the Internationalization Success of Companies. Journal of Physics: Conference Series, 1108 (012038). pp. 1-7. ISSN 1742-6588

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Official URL: https://doi.org/10.1088/1742-6596/1108/1/012038



Abstract

The internationalization started to be seen as an opportunity for many companies. This is one of the most crucial growth strategies for companies. Internationalization can be defined as a corporative strategy for growing through foreign markets. It can enhance the product lifetime and improve productivity and business efficiency. However, there is no general model for a successful international company. Therefore, the success of an internationalization procedure must be estimated based on different variables such as the status, strategy, and market characteristics of the company. In this paper, we try to build a model in evaluating the internationalization success of a company based on existing past data by using Support Vector Machines. The results are very encouraging and show that Support Vector Machines can be a useful tool in this sector. We found that Support Vector Machines achieved 81.36% accuracy rate with RBF Kernel, 80% training set, and


Item Type:Article
Subjects:Social sciences > Economics > Accounting
Social sciences > Economics > Business enterprises
Social sciences > Economics > Stock exchanges
ID Code:60261
Deposited On:29 Apr 2020 11:50
Last Modified:29 Apr 2020 11:50

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